Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/137997
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dc.contributor.authorWee, Jun Haoen_US
dc.date.accessioned2020-04-21T08:22:42Z-
dc.date.available2020-04-21T08:22:42Z-
dc.date.issued2020-
dc.identifier.urihttps://hdl.handle.net/10356/137997-
dc.description.abstractVisual localization related technology has been deeply researched in the recent years, with increasing development in the field of robotics and autonomous vehicle. The project aims to develop an embedded place recognition system to aid navigation in an indoor environment. The FastABLE algorithm was adopted to provide the vision-based methods suitable for mobile devices. The FastABLE algorithm utilizes a set of test and training image sequences to run low level binary sequence extraction using the global binary descriptor and fast matching technique. This meets the requirement of low memory and computational cost to develop a visual navigation system that runs on embedded platforms. The report entails the testing and optimization process of the FastABLE algorithm and the FastABLE android application. The experimental results from the optimized FastABLE android application were subsequently evaluated, achieving average processing time of 1minute 40seconds and average accuracy rate of 48%.en_US
dc.language.isoenen_US
dc.publisherNanyang Technological Universityen_US
dc.relationSCSE19-0119en_US
dc.subjectEngineering::Computer science and engineering::Computing methodologies::Computer graphicsen_US
dc.subjectEngineering::Computer science and engineering::Computing methodologies::Image processing and computer visionen_US
dc.titlePlace recognition for indoor navigationen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorLam Siew Keien_US
dc.contributor.schoolSchool of Computer Science and Engineeringen_US
dc.description.degreeBachelor of Engineering (Computer Engineering)en_US
dc.contributor.supervisoremailassklam@ntu.edu.sgen_US
item.grantfulltextrestricted-
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Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)
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